The mass of data collected each day is becoming increasingly great. Currently, studies estimate that the quantity of information in the world is doubling every twenty months. The web and the digital libraries are giving birth to new issues in the fields of databases (DB) and information retrieval (IR) within these databases. In many applications, it is becoming important, even necessary, to make access to the information easier through systems for assisting in web browsing, systems for assisting in the formulation of requests for searches in the databases, for filtering, customizing and personalizing this information.
The prior art discloses various systems and techniques for searching for images or information. The conventional methods for image retrieval are usually based on principles related to linguistic indexing techniques (keywords) (ie, a pre-annotation text linked to images) without taking into account the information content or structural description such as the texture, the color, the density, the shape, the latent contours, etc., for image searches in a database.
Most of the methods use only the keywords associated with the images to make the classification. They also usually use classification techniques such as the averaging algorithms known by the abbreviated expression “k-means” in which the number of classes to be found and the centers (mobile) of these classes must be defined arbitrarily. Such techniques imply an instability in the results depending on the original parameter settings (sensitivity of the algorithms to the starting points). Other methods use other parameters such as the color or the texture separately without combining them and they do not include any backtracking to refine the results obtained results.